Neuronal mechanisms encoding global-to-fine information in inferior-temporal cortex
Sugase et al. found that global information is represented at the initial transient firing of a single face-responsive neuron in inferior-temporal (IT) cortex, and that finer information is represented at the subsequent sustained firing. A feed-forward model and an attractor network are conceivable...
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Published in | Journal of computational neuroscience Vol. 18; no. 1; pp. 85 - 103 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
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United States
Springer Nature B.V
01.01.2005
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Abstract | Sugase et al. found that global information is represented at the initial transient firing of a single face-responsive neuron in inferior-temporal (IT) cortex, and that finer information is represented at the subsequent sustained firing. A feed-forward model and an attractor network are conceivable models to reproduce this dynamics. The attractor network, specifically an associative memory model, is employed to elucidate the neuronal mechanisms producing the dynamics. The results obtained by computer simulations show that a state of neuronal population initially approaches to a mean state of similar memory patterns, and that it finally converges to a memory pattern. This dynamics qualitatively coincides with that of face-responsive neurons. The dynamics of a single neuron in the model also coincides with that of a single face-responsive neuron. Furthermore, we propose two physiological experiments and predict the results from our model. Both predicted results are not explainable by the feed-forward model. Therefore, if the results obtained by actual physiological experiments coincide with our predicted results, the attractor network might be the neuronal mechanisms producing the dynamics of face-responsive neurons. |
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AbstractList | Sugase et al. found that global information is represented at the initial transient firing of a single face-responsive neuron in inferior-temporal (IT) cortex, and that finer information is represented at the subsequent sustained firing. A feed-forward model and an attractor network are conceivable models to reproduce this dynamics. The attractor network, specifically an associative memory model, is employed to elucidate the neuronal mechanisms producing the dynamics. The results obtained by computer simulations show that a state of neuronal population initially approaches to a mean state of similar memory patterns, and that it finally converges to a memory pattern. This dynamics qualitatively coincides with that of face-responsive neurons. The dynamics of a single neuron in the model also coincides with that of a single face-responsive neuron. Furthermore, we propose two physiological experiments and predict the results from our model. Both predicted results are not explainable by the feed-forward model. Therefore, if the results obtained by actual physiological experiments coincide with our predicted results, the attractor network might be the neuronal mechanisms producing the dynamics of face-responsive neurons. |
Author | Okada, Masato Sugase-Miyamoto, Yasuko Yamane, Shigeru Matsumoto, Narihisa |
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BackLink | https://www.ncbi.nlm.nih.gov/pubmed/15789171$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Face Humans Models, Neurological Neurons - physiology Temporal Lobe - cytology Temporal Lobe - physiology Time Factors Visual Perception - physiology |
Title | Neuronal mechanisms encoding global-to-fine information in inferior-temporal cortex |
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